Multiscale full convolutional network feature fusion-based crowd counting method
A fully convolutional network and crowd counting technology, applied in biological neural network models, calculations, computer components, etc., can solve problems such as irregular distribution of crowds, achieve strong practicability, good robustness, and overcome occlusion effects
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[0039] A crowd counting method based on multi-scale fully convolutional network feature fusion provided in this embodiment includes the following steps:
[0040] S1: Input a picture and enter three branch networks respectively to obtain feature maps of different scales; the specific operations are:
[0041] a) First convert the picture with the head position label of the person into a crowd density map, if there is a head position at the pixel point x i , denoting it as δ(x-x i ), then the image with the head position markers of N people can be expressed as the functional formula (1):
[0042]
[0043] b) Combine the functional formula (1) with the Gaussian kernel G σ Perform convolution to obtain the density estimation function (2):
[0044] F(x)=H(x)*G σ (x) (2)
[0045] c) Automatically determine the propagation parameter σ of each person based on the average distance data from its neighbors, if the distance from each head in a given image to its k nearest neighbors...
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